1. Field of the Invention
The invention relates generally to methods for detecting analytes such as proteins, peptides, nucleic acids, ligands, antigens, lipids, enzymes, and other molecules in simple and complex systems.
2. Description of the Background
The disclosures referred to herein to illustrate the background of the invention and to provide additional detail with respect to its practice are incorporated herein by reference and, for convenience, are numerically referenced in the following text and respectively grouped in the appended bibliography.
A device that can be used to monitor gene expression rapidly in single cells would have several important applications. For example, surgeons often rely on histological methods to distinguish tumor and normal tissues during surgery to remove cancers. These methods serve well when the morphology of the abnormal and normal cells is readily distinguished. Unfortunately, the borders of many tumors are not always well defined and do not provide clear landmarks that can be used to guide surgery. Further, it may be difficult to gauge the characteristics of the tumor even after sections have been stained with histological dyes. This can lead to unnecessary surgery during efforts to remove all the cancerous tissue. Indeed, some surgery for breast cancer involves removing lymph nodes to stage the cancer even though there often is no evidence that this additional surgery will be of significant benefit. Application of a technique that has the ability to monitor gene expression in these frozen sections would have considerable application during surgery to guide the procedure. It would also be useful to guide the type of therapy that is to be used following surgery.
Recent advances in genetics have provided the basis by which physicians and scientists have gained new insights into cell function. Bioinformatic analysis suggests that humans have 30-40 thousand genes [1;2] that are transcribed, spliced, and edited to yield 100 thousand mRNAs detected as expressed sequence tags [3]. This information has permitted the design of microarrays capable of monitoring thousands of gene products at one time [4;5]. Microarray technology is being applied widely to characterize changes in gene expression patterns that are associated with various tumors and with the prognosis of tumor therapy [5-7]. Indeed, there is considerable hope that the results of these studies will enable a more accurate classification of tumors and thereby guide the choice of therapy following surgery. One benefit of this may be a reduction in unnecessary chemotherapy or radiotherapy [5], procedures that often make patients ill and that may even be a source of malignancies later in life [8].
Further technical advances in measurements of gene expression products are required to take full advantage of the new information that is being made available from microarray measurements. Tumors are often quite complex and contain endothelial cells, fibroblasts, lymphocytes, and other cell types in addition to transformed cells. Microarray analyses of whole tumor tissues detect expression products of these cell types simultaneously [4;5], a phenomenon that confounds the association of particular gene expression patterns with specific tumor cells. These analyses can be further compromised by the presence of different types of tumor cells within the sample. Nonetheless, despite this complexity, gene expression patterns detected in some tumors are correlated highly with five-year survival rates [5] and this information can be used to facilitate tumor classification, the major parameter used to decide how patients are treated.
The massive amount of data obtained during microarray analysis is extremely valuable but it is confounded by the presence of gene products that have been obtained from multiple cell types. It can also be time-consuming to obtain and, because it contains so much information, can be difficult to interpret accurately. Results of array analyses indicate that it not necessary to monitor the expression of all possible genes to classify the tumor accurately [5;9]. In fact, as exemplified by findings made from studies of colon carcinomas, a majority of which have a preponderance of mutations of the APC and p53 genes [10], it appears that analysis of relatively few gene products would be adequate to classify tumors. The types of genes to be monitored can be determined by taking advantage of information that is usually known at the time of surgery, such as the location of the tumor (i.e., mammary gland, prostate, colon, lung, brain, etc.). The technology described here permits one to measure the expression of several gene products in single cells of frozen sections that are routinely prepared during surgical procedures. By focusing on genes whose expression has been found in microarray and other analyses to be most characteristic of a given tumor type, it will be possible to classify the tumor accurately. The devices taught here permit this information to be determined in a rapid fashion and can be used to form the basis of instant decisions needed for patient care.
The cells in a cancer have altered properties that enable them to evade apoptotic mechanisms that normally limit cell growth. Some of these include checks on the integrity of their genome and, when these are lost or become non-functional, cancer cells tend to accumulate mutations that make them more aggressive. Since not all the cells of a tumor have the same mutations, the tumor can be heterogeneous. The heterogeneity of some tumors may even be due to the fact that they have originated from several different cells, not just a single cell. Thus, to classify the tumor accurately, it is best to assess gene products from individual cells so that the degree of heterogeneity can be ascertained. It is also important to detect the existence and location of even a small number of cells that have reduced sensitivity to natural regulatory mechanisms. The ability to do so would enable pathologists and surgeons to learn if the tumor contains cells that have characteristics indicative of a more advanced stage of cancer as well as to learn where they are within the tumor. If this information were available at the time of surgery, it would enable the surgeon to tailor the surgical procedure appropriately for each patient. For example, the absence of these cells might indicate that it would not be essential to remove nearby or distant lymph nodes that are not part of the tumor. In contrast, the presence of a few advanced cells in a small otherwise unremarkable tumor might be grounds for more extensive surgery. Thus, it would be desirable to have a sensor that could quantify gene expression rapidly in single cells of frozen sections obtained at the time of surgery. Furthermore, this information should also affect the choice of post-surgical treatment such as chemotherapy and/or radiation therapy.
The therapeutic benefits of identifying cells that have altered genotypes and/or phenotypes that lead to pathological states have been recognized for many years. The need to classify these cells has led to developments of several methods for examining cells that range from simple staining procedures to highly refined approaches for identifying specific genes and gene products within the cell. Increased knowledge of cell function offers a greatly expanded number of markers that can be used to assess the pathological status of single cells.
Several methods have been developed to study gene function in individual cells. Fluorescence Activated Cell Sorting (FACS) methods have permitted individual cells to be isolated from complex cellular mixtures based on the use of antibodies to a single surface protein. This method requires disrupting tissues into their component cells, which is a time-consuming process that makes FACS analysis poorly suited for use as a routine surgical procedure. Techniques such as Fluorescent in situ Hybridization (FISH) are sufficient to detect single genes within cells of a tissue. The most sensitive of these techniques require considerable tissue preparation, however, and are not sufficiently rapid for routine use during surgery. Furthermore, the intrinsic fluorescence in cells and other factors often contribute to high background. This makes it essential to perform several time-consuming internal controls without which it would be impossible to interpret the analysis. Other properties of fluorescence, such as the ability of adjacent fluorophores to interact with one another, a process known as Fluorescent Resonant Energy Transfer (FRET), have been used to facilitate analyses of gene expression. For example it has been found that fluorescent oligonucleotides can be used to detect mRNA products of single genes cells based on the abilities of the oligonucleotides to bind to adjacent portions of the mRNA [11]. Nonetheless, these techniques can be plagued by the high intrinsic fluorescence of cells. While it is possible to circumvent this problem using time-resolved methods [12], this increases the complexity of the method substantially at the expense of assay sensitivity. In addition, there is a need to get the fluorophores into the cells where they can interact with the mRNA. Thus, this approach is not practical for routine examination of tissue sections. Efforts have also been made to monitor gene products using fiber optic techniques [13]. These methods are also not applicable to tissue sections and suffer from a very slow response time.
In summary, knowledge of the gene products that are associated with different pathologies is accumulating rapidly. The public availability of the sequence of the human genome and advances in microarray technology has permitted the simultaneous semi-quantitative measurements of large numbers of gene products. Array procedures have been used to characterize changes in gene expression in several types of normal and abnormal tissues. Indeed, comparisons of gene expression patterns in tumor tissues with tumor recurrence and long-term survival of patients following surgery, chemotherapy, and/or radiation have enabled predictions about the types of therapies that are most likely to be beneficial [4]. As noted earlier, array procedures are not readily adapted to analyses of single cells. Consequently, the data generated by application of this technique are confounded by the presence of analytes in non-tumor cells as well as by the fact that many tumors contain different types of abnormal cells. This makes it difficult to associate gene expression with particular cells in even a semi-quantitative fashion. Furthermore, array analysis is time-consuming and not suited for the rapid estimation of gene expression while the patient is in the operating room. Measurements of gene expression in single cells within the tumor would be of considerable value for classifying the tumor, a key component used to make informed decisions about the extent of surgery and subsequent therapies. It would also be applicable during research to learn which gene expression products are most likely to have predictive value. Finally, it would also be useful for studies of cell function during complex processes such as those that occur during development and cellular differentiation.